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[('5', 0.12793059870235002), ('8', 0.12539646467821697), ('4', 0.12509737486793587), ('6', 0.12470234839853608), ('3', 0.12467331676337925), ('7', 0.12441254825093238), ('11', 0.12401867309944531), ('9', 0.12376867523920407)] |
[['5', '8', '4', '6', '3', '7', '11', '9']] |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
question: ['How many balloons are inside the party shop or balloon store?'], responses:['100'] |
[('100', 0.1277092174007614), ('120', 0.12519936731884676), ('88', 0.12483671971182599), ('80', 0.12474858811112934), ('60', 0.12457749608485191), ('99', 0.1243465850330014), ('90', 0.12430147627057883), ('101', 0.12428055006900451)] |
[['100', '120', '88', '80', '60', '99', '90', '101']] |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 1.5923e-08, 1.5449e-09, 5.8052e-07, 4.4658e-09, 7.0826e-09, |
7.2313e-10, 5.2832e-08], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
yes ************* |
['yes', 'congratulations', 'no', 'honey', 'solid', 'right', 'candle', 'chocolate'] tensor([1.0000e+00, 1.5923e-08, 1.5449e-09, 5.8052e-07, 4.4658e-09, 7.0826e-09, |
7.2313e-10, 5.2832e-08], device='cuda:2', grad_fn=<SelectBackward0>) |
question: ['Does the right image feature multiple canoes heading forward at a right angle?'], responses:['no'] |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(1.5449e-09, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(7.1371e-07, device='cuda:2', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=LEFT,question='How many birds are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} <= 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('no', 0.1313955057270409), ('yes', 0.12592208734904367), ('no smoking', 0.12472972590078177), ('gone', 0.12376514658020793), ('man', 0.12367833016285167), ('meow', 0.1235796378467502), ('kia', 0.12347643720898455), ('no clock', 0.12345312922433942)] |
[['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock']] |
torch.Size([13, 3, 448, 448]) |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
tensor([9.6989e-01, 2.2985e-08, 3.0035e-02, 6.9336e-05, 9.1004e-09, 8.7744e-07, |
3.2673e-08, 3.9001e-08], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
5 ************* |
['5', '8', '4', '6', '3', '7', '11', '9'] tensor([9.6989e-01, 2.2985e-08, 3.0035e-02, 6.9336e-05, 9.1004e-09, 8.7744e-07, |
3.2673e-08, 3.9001e-08], device='cuda:3', grad_fn=<SelectBackward0>) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(6.9336e-05, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(0.9999, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many glass panes are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 6') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([7, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3404 |
question: ['How many birds are in the image?'], responses:['2'] |
tensor([9.2365e-01, 1.2363e-02, 2.8627e-04, 1.0200e-02, 2.0692e-02, 2.7455e-03, |
2.9206e-02, 8.5674e-04], device='cuda:1', grad_fn=<SoftmaxBackward0>) |
100 ************* |
['100', '120', '88', '80', '60', '99', '90', '101'] tensor([9.2365e-01, 1.2363e-02, 2.8627e-04, 1.0200e-02, 2.0692e-02, 2.7455e-03, |
2.9206e-02, 8.5674e-04], device='cuda:1', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:1', grad_fn=<DivBackward0>), False: tensor(0., device='cuda:1', grad_fn=<MulBackward0>), 'Execute Error': tensor(5.9605e-08, device='cuda:1', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many trees are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 2') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)] |
[['2', '3', '4', '1', '5', '8', '7', '29']] |
torch.Size([13, 3, 448, 448]) |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
question: ['How many glass panes are in the image?'], responses:['3'] |
[('3', 0.12809209985493852), ('4', 0.12520382509374006), ('1', 0.1251059160028928), ('5', 0.12483070991268265), ('8', 0.12458076282181878), ('2', 0.12413212281858195), ('6', 0.1241125313968017), ('12', 0.12394203209854344)] |
[['3', '4', '1', '5', '8', '2', '6', '12']] |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
torch.Size([7, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3403 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3404 |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3404 |
question: ['How many trees are in the image?'], responses:['Many'] |
[('many', 0.12680051474066337), ('few', 0.12559712123098582), ('several', 0.12545126119006317), ('blinds', 0.12452572291517987), ('moss', 0.12441899466837554), ('rainbow', 0.1244056457460399), ('kite', 0.12440323404357946), ('directions', 0.12439750546511286)] |
[['many', 'few', 'several', 'blinds', 'moss', 'rainbow', 'kite', 'directions']] |
dynamic ViT batch size: 13, images per sample: 13.0, dynamic token length: 3404 |
torch.Size([13, 3, 448, 448]) knan debug pixel values shape |
tensor([1.0000e+00, 1.6212e-08, 3.4839e-07, 4.8750e-12, 3.2241e-11, 2.9082e-10, |
1.3161e-10, 3.1428e-07], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
no ************* |
['no', 'yes', 'no smoking', 'gone', 'man', 'meow', 'kia', 'no clock'] tensor([1.0000e+00, 1.6212e-08, 3.4839e-07, 4.8750e-12, 3.2241e-11, 2.9082e-10, |
1.3161e-10, 3.1428e-07], device='cuda:0', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.6212e-08, device='cuda:0', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:0', grad_fn=<DivBackward0>), 'Execute Error': tensor(7.1526e-07, device='cuda:0', grad_fn=<DivBackward0>)} |
ANSWER0=VQA(image=RIGHT,question='How many vases are in the image?') |
ANSWER1=EVAL(expr='{ANSWER0} == 1') |
FINAL_ANSWER=RESULT(var=ANSWER1) |
torch.Size([5, 3, 448, 448]) |
tensor([9.9175e-01, 8.1751e-03, 1.1807e-07, 6.1040e-05, 1.2685e-07, 2.4344e-08, |
1.0778e-05, 5.4181e-06], device='cuda:3', grad_fn=<SoftmaxBackward0>) |
3 ************* |
['3', '4', '1', '5', '8', '2', '6', '12'] tensor([9.9175e-01, 8.1751e-03, 1.1807e-07, 6.1040e-05, 1.2685e-07, 2.4344e-08, |
1.0778e-05, 5.4181e-06], device='cuda:3', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0778e-05, device='cuda:3', grad_fn=<DivBackward0>), False: tensor(1.0000, device='cuda:3', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:3', grad_fn=<DivBackward0>)} |
question: ['How many vases are in the image?'], responses:['2'] |
[('2', 0.12961991198727602), ('3', 0.12561270547489775), ('4', 0.12556127085987287), ('1', 0.1254920833223361), ('5', 0.12407835939022728), ('8', 0.124024076973589), ('7', 0.12288810153923228), ('29', 0.12272349045256851)] |
[['2', '3', '4', '1', '5', '8', '7', '29']] |
torch.Size([5, 3, 448, 448]) knan debug pixel values shape |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 |
tensor([1.0000e+00, 3.4321e-08, 7.7787e-09, 3.2563e-07, 2.2678e-10, 4.7538e-10, |
1.0445e-09, 8.0876e-11], device='cuda:2', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 3.4321e-08, 7.7787e-09, 3.2563e-07, 2.2678e-10, 4.7538e-10, |
1.0445e-09, 8.0876e-11], device='cuda:2', grad_fn=<SelectBackward0>) |
ζεηζ¦ηεεΈδΈΊ: {True: tensor(1.0000, device='cuda:2', grad_fn=<DivBackward0>), False: tensor(4.3928e-08, device='cuda:2', grad_fn=<DivBackward0>), 'Execute Error': tensor(0., device='cuda:2', grad_fn=<DivBackward0>)} |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 |
dynamic ViT batch size: 5, images per sample: 5.0, dynamic token length: 1349 |
tensor([1.0000e+00, 3.5012e-06, 9.0750e-10, 8.0585e-07, 8.4480e-10, 1.1093e-10, |
6.3856e-10, 2.2946e-09], device='cuda:0', grad_fn=<SoftmaxBackward0>) |
2 ************* |
['2', '3', '4', '1', '5', '8', '7', '29'] tensor([1.0000e+00, 3.5012e-06, 9.0750e-10, 8.0585e-07, 8.4480e-10, 1.1093e-10, |
6.3856e-10, 2.2946e-09], device='cuda:0', grad_fn=<SelectBackward0>) |
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